Scientific Method —

An in-silico study that got all over the lab

Computational screening of potential new catalysts for the hydrogen evolution …

I've said it twice in the past fewweeks:
we live in interesting times for computational scientists and
engineers. We are at a period where experimental interest and
computational ability have intersected, the latest example coming from
the world of
heterogeneous catalysis. A very common heterogeneous catalyst
is
a simple metal surface—nickel, platinum, and even iron are
common
examples—the catalytic activity arises from the atoms on the
surface. These catalysts work by having the reactants adsorb
onto the surface, where the metal—while not participating in the
reaction—changes the reaction energy landscape. This
makes it easier for
the reactants to react forming the product, which will then dissociate
and go on its merry way. One of the real tricks is
determining what material surfaces will be catalytically active and
how active they will be, if at all. While there is a whole
alphabet soup of physical surface characterization
methods—AFM,
STM, SFA—and an equal litany of spectroscopic techniques to
study
adsorption dynamics and surface chemistry—IR, NMR, AES, XPS,
UPS—none, to my knowledge, can tell a priori the
potential catalytic activity of a surface in the absence of
a reaction study. Without a convenient way to test
for
potential activity, designing or discovering new catalytic
materials is a daunting task.

In other fields where the main thrust of research is finding new
materials for a specific purpose, combinatorial synthesis
approaches have been used with quite some success: we reported
on
just such a study last month.
In a recent edition of Nature
Materials a team set up a computational
combinatorial synthesis approach to finding novel materials to be used
as a catalyst for the hydrogen evolution reaction (HER). By
analyzing decades of previous experimental data, the researchers found
that the catalytic activity for a material being used to carry out the
HER correlated well with the Gibbs free energy of hydrogen adsorption
onto the material. They illustrated that the activity will be
at
a maximum when the free energy of hydrogen adsorption is at or near
zero. With this in mind, they set about finding surfaces
where
this condition was true. In my last simulation post, I made
mention that the only way to know you are simulating something exactly
right is if you solve the quantum mechanical equations for every
electron involved. This is an impossible task for all
but the
simplest systems; however, that does not mean that there are no
workarounds. Using an technique known as densityfunctionaltheory
(DFT)
the research team solved for the electronic structure of a small slab
of atoms to answer the question of whether or not they could make a
good catalyst for the HER by computing the free energy of hydrogen
adsorption on the surface.

The study picked 16 elements and laid them on a square grid, where
each point on the grid represented a surface alloy of the
metals for that
row and column,
giving 256 potential candidates for study. Out of the 256
potential catalysts, 49 showed promise by having a computed free energy
of hydrogen adsorption of less than 0.1 and greater than -0.1.
In addition to finding materials that may be favorable in
catalyzing the HER, they also computed whether or not these potential
materials would be stable under necessary conditions.
Several,
including BiPt (Bismuth and Platinum), PtRu (Platinum and Ruthenium),
IrRe (Iridium and Rhenium), and RhRe (Rhodium and Rhenium) among
others were found to be both potentially active and
theoretically stable. Of this final pool, the authors focused
their work on BiPt, due in part to the contrast between the two
component elements of the alloy—bismuth is not catalytically
active
at all, while platinum is one of the more active and more commonly used
catalysts—and due to the relatively high predicted activity
level.

Previously, experimental studies have tested two forms of BiPt as
potential catalysts, bulk metallic PtBi or PtBi2,
and
irreversibly adsorbed bismuth on platinum (Pt-Biir).
The
previous work showed that adsorbed bismuth poisons the platinum,
reducing its catalytic activity to near zero. However, this
is
not an apples-to-apples comparison. The in-silico study
looked a a surface alloy of bismuth on platinum, not an irreversibly
adsorbed bismuth on platinum mixture. To attempt to prove
their prediction the
authors then left the computer behind and headed into the lab.
There, they were able to synthesize the surface alloy that
they had designed in the simulations and could then carry out the HER
over it to measure its catalytic activity. What they found
was surprising: the BiPt surface alloy they created had almost a 50
percent greater
activity
than platinum alone, the current "gold standard" for catalytic
activity. By combining two traditional lines of
thought—computer simulations and laboratory
experiments—the
authors managed to successfully predict a new compound that should be a
good catalyst and they were able to synthesize it and prove that it is
indeed a better catalyst that what is currently used. It is
this synthesis of two fields of thought that will hopefully allow us to
do better science, faster, and make discoveries at an ever-increasing
pace.

Matt Ford
Matt is a contributing writer at Ars Technica, focusing on physics, astronomy, chemistry, mathematics, and engineering. When he's not writing, he works on realtime models of large-scale engineering systems. Emailzeotherm@gmail.com//Twitter@zeotherm